scholarly journals Spatio-temporal analysis of Lençóis Maranhenses between 1984 and 2014 using orbital remote sensing

2016 ◽  
Vol 9 (1) ◽  
pp. 280-295
Author(s):  
Thiago Diniz Araujo ◽  
Eliana Lima da Fonseca
Keyword(s):  
Remote Sensing ◽  
Temporal Analysis ◽  
Spatio Temporal

Spatio-temporal Analysis of Shoreline Positional Change of Ondo State Coastline Using Remote Sensing and GIS: A Case Study of Ilaje Coastline at Ondo State in Nigeria

2021 ◽  
Author(s):  
Akinola Adesuji Komolafe ◽  
Paul Ayodeji Apalara ◽  
Matthew Olomolatan Ibitoye ◽  
Abiodun Olufemi Adebola ◽  
Idowu Ezekiel Olorunfemi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Temporal Analysis ◽  
Remote Sensing And Gis ◽  
Positional Change ◽  
Ondo State ◽  
Spatio Temporal

scholarly journals SPATIO-TEMPORAL DYNAMIC OF LAND DEGRADATION USING REMOTE SENSING-BASED INDEX

AGROFOR ◽  
2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Seyed Hamidreza SADEGHI ◽  
Fahimeh MIRCHOOLI ◽  
Abdulvahed KHALEDI DARVISHAN
Keyword(s):  
Remote Sensing ◽  
Land Degradation ◽  
Net Primary Productivity ◽  
Temporal Analysis ◽  
Mean Value ◽  
Annual Rainfall ◽  
Landsat Images ◽  
Policy Makers ◽  
Use Efficiency ◽  
Spatio Temporal

Land degradation is the major issue which affect watershed sustainability and following social, economic and environmental of livelihood people. So, early detection of land degradation is necessary for policy-makers to make appropriate decision. In this way, remote sensing method is a candidate choice for assessments and monitoring. In this study, land degradation was assessed using Rain-Use Efficiency (RUE) in the Shazand Watershed, Iran in 1986, 1998, 2008 and 2016. Thus, annual rainfall was calculated using inverse distance weight (IDW), net primary productivity (NPP) were calculated using Landsat images. The results indicated that RUE had increasing and then decreasing trends which were 10.66, 33.77, 20.03 and 9.47 kg C ha-1 yr-1. The results also illustrate that the mean value of RUE in different land uses varied between the irrigated land and orchard that had the highest value and outcrop dominant areas and bareland had the lowest value of RUE among land use categories. It is also established that spatio-temporal analysis of RUE can provide valuable information about the trend of watershed’s sustainability over years.

scholarly journals Highlighting the Sustainability Implications of Urbanisation: A Comparative Analysis of Two Urban Areas in Ghana

Land ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 300 ◽  
Author(s):  
Kwasi Anarfi ◽  
Ross A. Hill ◽  
Chris Shiel
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Land Tenure ◽  
Urban Areas ◽  
Local Level ◽  
Population Data ◽  
Temporal Analysis ◽  
Resource Extraction ◽  
Market Forces ◽  
Spatio Temporal

Ghana is urbanising rapidly, and over half of the country’s population have lived in urban areas since 2010. Although research has proliferated to explore Ghana’s urbanisation, there is a dearth of research that holistically explores the wider sustainability implications of urbanisation, offers comparative perspectives in the context of large and smaller urban areas, and provides a perspective of local level urbanisation in the context of resource extraction (mining). This study comparatively assesses two urban areas in Ghana (Kumasi and Obuasi), by conducting a spatio-temporal analysis of land cover change through remote sensing and by analysing demographic change through a synthesis of published population data, in order to highlight the sustainability implications of urbanisation. The results show that urbanisation has been rapid, and has resulted in changes in land cover and demography in Kumasi and Obuasi. The sustainability implications of urbanisation are identified to include limited economic opportunities, socio-spatial segregation, and destruction of natural vegetation. The evidence in this study provides insights into urbanisation in Ghana, and suggests that the positive sustainability impacts of urbanisation may be eroded by how factors such as market forces and land tenure interact at the local level.

scholarly journals Spatio-Temporal Analysis of Satellite Imagery (NDVI) to Identify Terroir and Vineyard Yeast Differences According to Appellation of Origin (AOP) and Biogeographic Origin

J ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 244-256
Author(s):  
Sergio Vélez ◽  
Enrique Barajas ◽  
Pilar Blanco ◽  
José Antonio Rubio ◽  
David Castrillo
Keyword(s):  
Remote Sensing ◽  
Satellite Imagery ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Temporal Analysis ◽  
Landsat 8 ◽  
Appellation Of Origin ◽  
Core Concepts ◽  
Spatio Temporal ◽  
Plant Habitat

Terroir is one of the core concepts associated with wine and presumes that the land from which the grapes are grown, the plant habitat, imparts a unique quality that is specific to that growing site. Additionally, numerous factors can influence yeast diversity, and terroir is among the most relevant. Therefore, it can be interesting to use Remote Sensing tools that help identify and give helpful information about the terroir and key characteristics that define the AOP (Appellation of Origin). In this study, the NDVI (Normalized Difference Vegetation Index) calculated from Landsat 8 imagery was used to perform a spatio-temporal analysis during 2013, 2014, and 2015 of several vineyards belonging to four different AOP in Galicia (Spain). This work shows that it is possible to use Remote Sensing for AOP delimitation. Results suggest: (i) satellite imagery can establish differences in terroir, (ii) the higher the NDVI, the higher the yeast species richness, (iii) the relationship between NDVI, terroir, and yeasts shows a stable trend over the years (Pearson’s r = 0.3894, p = 0.0119).

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